Skip to main content
SpringerLink
Log in

Toward the Application of Argumentation to Interactive Learning Systems

  • Conference paper
Argumentation in Multi-Agent Systems (ArgMAS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7543))

Included in the following conference series:

  • 448 Accesses

Abstract

This paper explores the application of argumentation dialogues to an Interactive Learning System (ILS). The goal of an ILS is to provide an adaptive learning experience for a student within a particular domain, where the system adjusts dynamically as the student makes mistakes and learns from them. The system needs to be able to represent beliefs about the student’s knowledge, and to update these beliefs as the student learns. The system also needs to have models of the domain and of an expert’s actions within the domain, in order to compare and evaluate the student’s actions. Finally, the system needs to provide appropriate feedback to the student, in such a way as to encourage learning. The work presented here describes a framework for such a system, built upon our earlier work on education dialogues.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Amgoud, L., Maudet, N., Parsons, S.: Modelling dialogues using argumentation. In: Proceedings of the 4th Conference on Multi-Agent Systems, Boston (2000)

    Google Scholar 

  2. Anderson, J.R.: The Architecture of Cognition. Harvard University Press (1983)

    Google Scholar 

  3. Anderson, J.R., Skarecki, E.: The automated tutoring of introductory programming. Communications of the ACM 29(9), 842–849 (1986)

    Article  Google Scholar 

  4. Azhar, M.Q., Goldman, R., Sklar, E.I.: An agent-oriented behavior-based interface framework for educational robotics. In: Agent-Based Systems for Human Learning (ABSHL) Workshop at Autonomous Agents and Multi Agent Systems, AAMAS (2006)

    Google Scholar 

  5. Beck, J., Stern, M., Haugsjaa, E.: Applications of AI in Education. Crossroads 3(1), 11–15 (1996)

    Google Scholar 

  6. Beck, J.E., Chang, K.-M., Mostow, J., Corbett, A.: Does Help Help? Introducing the Bayesian Evaluation and Assessment Methodology. In: Woolf, B.P., Aïmeur, E., Nkambou, R., Lajoie, S. (eds.) ITS 2008. LNCS, vol. 5091, pp. 383–394. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  7. Conati, C., Gertner, A., VanLehn, K.: Using Bayesian Networks to Manage Uncertainty in Student Modeling. User Modeling and User-Adapted Interaction 12(4) (2002)

    Google Scholar 

  8. Corbett, A.T., Anderson, J.R.: The LISP Intelligent Tutoring System: Research in skill acquisition, pp. 73–109. Lawrence Erlbaum, Hillsdale (1992)

    Google Scholar 

  9. Erwin, B., Cyr, M., Rogers, C.B.: LEGO Engineer and ROBOLAB: Teaching Engineering with LabVIEW from Kindergarten to Graduate School. International Journal of Engineering Education 16(3) (2000)

    Google Scholar 

  10. Gertner, A.S., Conati, C., VanLehn, K.: Procedural help in Andes: Generating hints using a Bayesian network student model. In: Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 106–111. AAAI Press (1998)

    Google Scholar 

  11. Girle, R.: Commands in Dialogue Logic. In: Gabbay, D.M., Ohlbach, H.J. (eds.) FAPR 1996. LNCS, vol. 1085, pp. 246–260. Springer, Heidelberg (1996)

    Chapter  Google Scholar 

  12. Johnson, W.L., Rickel, J.W., Lester, J.C.: Animated pedagogical agents: Face-to-face interaction in interactive learning environments. International Journal of Artificial Intelligence in Education 11 (2000)

    Google Scholar 

  13. Kasurinen, J., Nikula, U.: Estimating programming knowledge with bayesian knowledge tracing. In: Proceedings of the 14th Annual ACM SIGCSE Conference on Innovation and Technology in Computer Science Education (ITiCSE), pp. 313–317. ACM, New York (2009)

    Chapter  Google Scholar 

  14. Lane, H.C., VanLehn, K.: A dialogue-based tutoring system for beginning programming. In: Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS), pp. 449–454. American Association for Artificial Intelligence Press (2004)

    Google Scholar 

  15. Lane, H., VanLehn, K.: Coached program planning: dialogue-based support for novice program design. In: Proceedings of the 34th SIGCSE Technical Symposium on Computer Science Education, pp. 148–152. ACM (2003)

    Google Scholar 

  16. Lazarus, R.S.: Cognition and Motivation in Emotion. American Psychologist 45(4), 352–367 (1991)

    Article  Google Scholar 

  17. LEGO Mindstorms, http://www.legomindstorms.com/

  18. Martin, J., Vanlehn, K.: Student assessment using bayesian nets. International Journal of Human-Computer Studies 42, 575–591 (1995)

    Article  Google Scholar 

  19. McBurney, P., Parsons, S.: Agent ludens: Games for agent dialogues. In: Proceedings of the AAAI Spring Symposium on Game Theoretic and Decision Theoretic Agents, Stanford, CA, USA (2001)

    Google Scholar 

  20. McBurney, P., Parsons, S.: Chance discovery using dialectical argumentation. In: Proceedings of the Workshop on Chance Discovery, Fifteenth Annual Conference of the Japanese Society for Artificial Intelligence, Matsue, Japan (2001)

    Google Scholar 

  21. McCalla, G.I., Greer, J.E.: Granularity-based reasoning and belief revision in student models. In: Student Models: The Key to Individualized Educational Systems, pp. 39–62. Springer, New York (1994)

    Google Scholar 

  22. Parsons, S., Wooldridge, M., Amgoud, L.: Properties and complexity of formal inter-agent dialogues. Journal of Logic and Computation 13(3), 347–376 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  23. Parsons, S., Sklar, E.: How Agents Alter Their Beliefs After an Argumentation-Based Dialogue. In: Parsons, S., Maudet, N., Moraitis, P., Rahwan, I. (eds.) ArgMAS 2005. LNCS (LNAI), vol. 4049, pp. 297–312. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  24. Robolab, http://www.ceeo.tufts.edu/robolabatceeo/

  25. Sklar, E.I., Richards, D.: Agent-based systems for human learners. Knowledge Engineering Review 25(2), 111–135 (2010)

    Article  Google Scholar 

  26. Sklar, E.: CEL: A Framework for Enabling an Internet Learning Community. Ph.D. thesis, Department of Computer Science, Brandeis University, Waltham, MA, USA (2000)

    Google Scholar 

  27. Sklar, E., Davies, M.: Multiagent simulation of learning environments. In: Fourth International Conference on Autonomous Agents and Multi Agent Systems, AAMAS (2005)

    Google Scholar 

  28. Sklar, E., Parsons, S.: Towards the Application of Argumentation-based Dialogues for Education. In: Proceedings of the Third International Conference of Autonomous Agents and Multi Agent Systems (AAMAS), pp. 1420–1421 (2004)

    Google Scholar 

  29. Sklar, E., Richards, D.: The use of agents in human learning systems. In: Fifth International Conference on Autonomous Agents and Multi Agent Systems, AAMAS (2006)

    Google Scholar 

  30. Spoelstra, M., Sklar, E.: Using simulation to model and understand group learning. Agent Based Systems for Human Learning, International Transactions on Systems Science and Applications 4(1) (2008)

    Google Scholar 

  31. VanLehn, K., Lynch, C., Schulze, K., Shapiro, J.A., Shelby, R., Taylor, L., Treacy, D., Weinstein, A., Wintersgill, M.: The Andes Physics Tutoring System: Lessons Learned. International Journal of Artificial Intelligence and Education 15(3) (2005)

    Google Scholar 

  32. VanLehn, K., Niu, Z., Siler, S., Gertner, A.S.: Student Modeling from Conventional Test Data: A Bayesian Approach without Priors. In: Goettl, B.P., Halff, H.M., Redfield, C.L., Shute, V.J. (eds.) ITS 1998. LNCS, vol. 1452, pp. 434–443. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  33. Walton, D.N., Krabbe, E.C.W.: Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning. State University of New York Press, Albany (1995)

    Google Scholar 

  34. Wei, F., Moritz, S.H., Parvez, S.M., Blank, G.D.: A student model for object-oriented design and programming. Journal of Computing Sciences in Colleges 20(5), 260–273 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept of Computer & Information Science, Brooklyn College, The City University of New York, 2900 Bedford Avenue, Brooklyn, NY, 11210, USA

    Elizabeth Sklar

  2. Dept of Computer Science, The Graduate Center, The City University of New York, 365 Fifth Avenue, New York, NY, 10016, USA

    Elizabeth Sklar & M. Q. Azhar

Authors
  1. Elizabeth Sklar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Q. Azhar
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Informatics, King’s College London, Strand Building S6.04, The Strand, WC2R 2LS, London, UK

    Peter McBurney

  2. Department of Computer and Information Science, Brooklyn College, City University of New York, 2900 Bedford Avenue, 11210, ^Brooklyn, NY, US

    Simon Parsons

  3. Masdar Institute of Science and Technology, P.O. Box 54224, Abu Dhabi, United Arab Emirates

    Iyad Rahwan

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sklar, E., Azhar, M.Q. (2012). Toward the Application of Argumentation to Interactive Learning Systems. In: McBurney, P., Parsons, S., Rahwan, I. (eds) Argumentation in Multi-Agent Systems. ArgMAS 2011. Lecture Notes in Computer Science(), vol 7543. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33152-7_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-33152-7_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33151-0

  • Online ISBN: 978-3-642-33152-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation